The intensification of China-US trade friction has posed significant uncertainties for China's outward foreign direct investment (OFDI). Existing studies predominantly employed regression analysis to identify the determinants of China's OFDI location choice, yet they primarily focused on the net effects of single variables, failing to reveal the role of interactions of multiple conditions in shaping China's OFDI location choices. Moreover, there is a lack of exploration of the location choice of China's OFDI in the context of China-US trade friction. This study applied the fuzzy-set qualitative comparative analysis (fsQCA) to investigate the configurational effects of multidimensional distances, market potential, and factor endowments of host countries on China's OFDI location choice in the context of China-US trade friction. The findings are as follows: 1) Four distinct pathways were identified before the China-US trade friction, whereas three distinct pathways were identified after the China-US trade friction, indicating the existence of multiple pathways for China's OFDI location choice, with differences in pathways before and after the breakout of China-US trade friction. 2) Before the China-US trade friction, innovation level was the most critical factor. However, in the context of China-US trade friction, market size and natural resources became paramount. The importance of political distance and market openness increased in China's OFDI location choices, while the influence of innovation level and economic freedom diminished. 3) Market size, factor endowments, and political distance exerted stronger impacts on capital-intensive OFDI, whereas technology-intensive OFDI was primarily influenced by natural resources and economic freedom. This study bridges the theoretical gap by addressing the lack of configurational analysis in traditional studies on China's OFDI location choices. Moreover, this article also provides practical insights for China to advance its "Going Global" strategy in the new era.

Lithography machines are the core equipment of semiconductor manufacturing and play a crucial role in technological revolution and economic transformation. Based on the global lithography machine trade data from 2007 to 2022 obtained from the UN Comtrade Database, this study employed network structural analysis and the temporal exponential random graph model (TERGM) to explore the characteristics of change and driving factors of the global lithography machine trade network. The results show that: 1) At the overall network level, the global lithography machine trade volume had continuously expanded from 2007 to 2022, with the network density, connectivity, and average degree first declining and then rising, the clustering coefficient steadily increasing, and both the average path length and network diameter decreasing. 2) At the individual network level, trade was highly concentrated among a few core economies in both imports and exports, with a trend toward import diversification and the emergence of secondary exporters. China's mainland had risen as the largest importer, while the export dominance of the Netherlands and Japan had strengthened, and the United States' export influence had weakened. 3) In terms of spatial organization, the global lithography equipment trade exhibited a "strong North-weak South" pattern, with the spatial center shifting eastward and intra-regional trade connections strengthening significantly. Meanwhile, the core-periphery structure had evolved from a U.S.-led unipolar system to a China-U.S. bipolar configuration, as trade linkages between the core and semi-core layers intensified while peripheral connections remained sparse. 4) With regard to the driving factors, the network was jointly shaped by endogenous structures, node attributes, and relational attributes, displaying reciprocity, path dependence, and the Matthew effect. Information and communication technology (ICT) levels, innovation output, and intellectual property protection promoted both imports and exports, while R&D investment mainly stimulated exports. Geographic, linguistic, and institutional proximities had positive effects, whereas the Wassenaar Arrangement significantly constrained network development. Overall, the driving mechanism had gradually shifted from capability-driven to structure-driven, highlighting the growing importance of endogenous structural effects. This study not only provides a new perspective for understanding the global lithography machine trade pattern but also offers empirical insights for China's trade and industrial policy in the lithography sector.

Research on the innovation geography of specialized, sophisticated, and innovative "little giant" enterprises is of great significance for promoting place-based cultivation of new-quality productivity. Based on patent data of coastal "little giant" enterprises from 2019 to 2023, this study measured their innovation level from the dual perspectives of innovation quantity and innovation quality, characterized their spatial and industrial distribution patterns, and revealed the typological features of innovation development across cities. The study found that: 1) The innovation quantity of "little giant" enterprises has been continuously increasing, showing a distinct spatial imbalance. Innovation activities were mainly concentrated in the Yangtze River Delta, the Pearl River Delta, and the Bohai Rim urban agglomerations. Innovation quantity also exhibited strong industrial concentration, primarily in the machinery and equipment manufacturing industry, high-tech service industry, and high-tech manufacturing industry. 2) Innovation quality has been steadily improving and demonstrated a more balanced spatial distribution; although innovation quality has risen across industries, substantial disparities remain. 3) The innovative development of coastal "little giant" enterprises can be categorized into four types—low quantity-low quality, low quantity-high quality, high quantity-low quality, and high quantity-high quality—with leading industries varying among different city types. Overall, the innovation development of coastal "little giant" enterprises featured quantitative agglomeration, qualitative balance, and industrial differentiation. Cities should tailor their development strategies to local conditions and take "little giant" enterprises as key drivers to cultivate new-quality productivity in a context-specific manner.

Lack of diversity of industrial structure and the high dependence on natural resources make resource-based cities exceptionally sensitive and vulnerable to internal and external shocks and disturbances. Scientifically measuring the economic resilience level of resource-based cities and identifying obstacles is a new way to enhance their sustainable development capabilities. Based on the relevant data of 110 resource-based cities from 2010 to 2022, a comprehensive evaluation system of "resistance and resilience capacity-adaptation and regulation capacity-transformation and development capacity" was constructed. The entropy method, GIS spatial analysis, and obstacle degree model were used to quantitatively analyze the temporal changes, spatial patterns, and obstacle factors of China's resource-based cities' economic resilience. The results show that: 1) The economic resilience level of resource-based cities had improved from 0.0679 to 0.1249, and it presented the characteristics of regeneration type > maturity type > growth type > decline type, but the growth rate of the growth-type cities was in a leading position, and there was a catch-up effect. 2) The economic resilience level of resource-based cities showed significant spatial differentiation, with a trend of eastern region > central region > western region > northeastern region. The economic resilience level of the eastern, central, and western regions had been increasing year by year, while the northeastern region showed abnormal fluctuations. The hotspot areas were distributed in the Huang-Huai-Hai region centered on Xuzhou, Jining, and so on, while the cold spot areas had shifted from the southwestern and northwestern regions to the northeastern region. 3) At the system level, the ability to resist and recover, as well as the ability to adapt and regulate, were the main obstacles to improving the economic resilience of resource-based cities. At the indicator level, insufficient wealth accumulation among residents, weak demands, unhealthy fiscal policies, and rigid constraints from industrial structure were important factors that impaired economic resilience. This study provides a scientific reference for enhancing the economic resilience of resource-based cities and formulating relevant resilience development policies.

The resilience of the human-sea economic system is an important basis for testing the health of the marine economic structure. Based on the adaptive cycle theory, we introduced the concept of social-ecological system resilience, defined the three-attribute resilience framework of environmental sensitivity, adaptive cycle capacity, and transformative ability, and constructed an evaluation framework for the adaptive cycle mechanism with potential, connectivity, and resilience dimensions. We applied the entropy weight TOPSIS method, adaptive cycle identification model, and spatial connection gravity model to analyze the spatiotemporal heterogeneity of the adaptive cycle and resilience of the human-sea economic system in the Bohai Rim region. The results show that: 1) From 2012 to 2022, the adaptability of the human-sea economic system in the Bohai Rim region to the cycle of "potential-connectivity-resilience" showed an overall upward trend, with significant spatial distribution differences. 2) From 2012 to 2022, cities around the Bohai Sea were in the development and protection stages of an adaptive cycle, in a positive cycle, with the southern Shandong urban agglomeration evolving from the development stage (r) to the protection stage (k). 3) The human-sea economic system of the Bohai Rim region showed a stable and concentrated spatiotemporal distribution of resilience, gradually forming a multi-regional development network structure in spatial connections, and integration with the strengthening of the connection between the central and southern urban patterns. This study provide theoretical reference and case support for the sustainable and high-quality development of marine economy in coastal cities.

Industrial co-agglomeration can promote green innovation, creating a combined effect where the whole is greater than the sum of its parts. However, the scales of the co-located industries can be very different and their co-evolution can be asynchronous. As a result, their interactions can be asymmetric. Does this asymmetry affect the positive impact of industrial co-agglomeration on green innovation? In this article, we propose that the asymmetric co-agglomeration can result in biased, nonlinear, and simultaneous effects on green innovation. We used the development of polluting and environmental industries in the Yangtze River Delta region from 2000 to 2022 as an example. We analogized the interactions between environmental and polluting industries to the predator-prey relationship. Accordingly, the Lotka-Volterra model was employed to identify the asymmetric characteristics (technology push and market pull). Then, we constructed a set of econometric models to test the impact of industrial co-agglomeration and its asymmetry on green innovation. The findings reveal that: 1) Of the cities in the Yangtze River Delta region, 80% witnessed the co-evolution between polluting and environmental industries, primarily driven by market pull from the polluting industry. Meanwhile, there were seven cities in which environmental industries could in turn push the development of polluting industries. 2) The asymmetric co-agglomeration led to biased effects on green innovation. The development of environmental industries has been able to promote the green innovation in the Yangtze River Delta region, and their co-agglomeration with polluting industries amplified its positive effects on green innovation. Polluting industries did not directly promote green innovation. Instead, they could contribute to green innovation via their co-agglomeration with green industries. Their effects increased as the green industries developed. 3) The asymmetric co-agglomeration led to nonlinear and simultaneous effects on green innovation. The asymmetry of industrial co-agglomeration changed its mechanism of influencing green innovation. In the context dominated by the market pull of polluting industries, both environmental and polluting industries would finally contribute to green innovation, although their development was asynchronous. In the context dominated by the technological push of environmental industries, environmental industries promoted the development of polluting industries. However, the positive effects of environmental industries will gradually decrease as the market demand changes.

Agricultural modernization and modernization of rural areas are interrelated and mutually promoting, which together constitute the core content of the overall rural revitalization. This study constructed an evaluation indicator system for modernization of agriculture and rural areas, and used the modified coupling coordination degree model, LISA time path, and P-VAR model to explore the regional differentiation patterns, spatiotemporal coordinated change characteristics, and interactive response relationships of the two at the county scale of Jilin Province during 2012-2022. The results show that: 1) The level of agricultural modernization and modernization of rural areas in Jilin Province has been improved, showing an overall gradient development and regional differentiation. Due to the path dependence on resource endowment and policy orientation, a spatial pattern of agricultural modernization strong in the west and weak in the east and modernization of rural areas high in the east and low in the west has been formed. 2) The overall coupling and coordination degree is relatively low. After 2018, it has been slightly improved under the impetus of policies. Regions with higher levels of modernization of rural areas also have higher coupling and coordination degrees. The coupling and coordination degree in the eastern region is generally higher than that in the traditional agricultural areas in the central and western regions. Spatially, it shows slow coordination growth, with poor regional linkages. There is a strong spatial integration and transfer inertia. 3) The development of agricultural modernization and modernization of rural areas in counties both have some degree of self-strengthening effect and inertia, and there exists a two-way nonlinear interactive relationship. Modernization of rural areas has a significant but short promoting effect on agricultural modernization, while agricultural modernization has a small but relatively lasting impact on modernization of rural areas. Finally, based on the regional characteristics, this article put forward targeted countermeasures and recommendations, with the aim of providing a scientific basis for the formulation of agricultural policies and rural development plans in Jilin Province and other major grain-producing areas.

Amid deepening globalization and informatization, urban networks arise from the interplay between the space of flows and the space of places, with a city's nodal position serving as a key indicator of its strength and influence. Responding to the turn toward a consumer society, amenities offer a fresh lens for urban innovation and transformation in China, but their role in shaping the structural change of urban networks has been underexplored. Building on a flow-place interaction framework, this study argues that rising quality-of-life demands make amenities a salient expression of place value—through locally distinctive culture and urban environmental quality—which, via a "differential perception-attention attraction" mechanism, draws flows and shifts cities' positions within the network. Empirically, Baidu Index data from 2012 to 2019 were used to analyze the nodal evolution of 280 Chinese cities through social network analysis. Furthermore, an urban amenity evaluation index was constructed across four dimensions—natural ecological environment, material environment, cultural and recreational environment, and social environment—and regression models were used to assess the impact of these factors on cities' network positions. The findings reveal that: 1) From 2012 to 2019, China's urban network evolved from a dual-core structure centered on Beijing and Shanghai to a pattern characterized by multiple coexisting cores, with cities such as Chengdu, Xi'an, and Chongqing demonstrating significantly high indegree centrality. 2) Amenity levels significantly promoted the change of cities' network status. 3) These effects were heterogeneous by region and city size—cities in central and western China were more likely to enhance their network positions through amenity development, while smaller cities relied more on the natural and cultural-recreational dimensions to improve their standing. These findings provide a novel theoretical perspective and empirical evidence for understanding how space of places contributes to the change of urban network structures. Moreover, they offer practical insights for local governments seeking to enhance place value and promote high-quality urban development through urban renewal initiatives.

Analyzing the patterns of change of ice and snow tourism destinations is a crucial foundation for promoting the sustainable development of China's ice and snow tourism industry. Taking Chongli District, Hebei Province as a case, this study applied the Butler's Tourism Area Life Cycle (TALC) theory in combination with the four-parameter Logistic model and the obstacle degree model to systematically explore the evolutionary characteristics and influencing mechanism of the destination's life cycle. The results indicate that: 1) The life cycle of Chongli's ice and snow tourism can be divided into four stages: the initial exploration stage (1996-2005), the rapid expansion stage (2005-2015), the Winter Olympics-driven stage (2015-2022), and the high-quality development stage (2022 to present), with a possible transition to a stagnation stage after 2030. 2) Different obstacle factors dynamically shaped the influencing mechanism of the life cycle across these stages. During the initial exploration and rapid expansion stages, grassroots development and local policies served as primary driving forces, while weak infrastructure and limited resource supply were major constraints. In the Winter Olympics-driven stage, both service and resource levels improved significantly, whereas the constraints shifted toward facility capacity and path dependency. In the high-quality development stage, issues of industrial structure lock-in and path dependence on the ice and snow industry become prominent, hindering a diversified transformation. 3) Based on the empirical findings, three strategies are proposed for the high-quality development stage: first, build a comprehensive international ice and snow tourism destination to promote high-quality development; second, construct an all-season tourism product system to optimize the industrial structure; and third, establish a talent system that combines internal cultivation and external recruitment to drive digital transformation and governance of ice and snow tourism destinations.

The change of business format networks in tourism destinations reflects the dynamic characteristics of regional coordinated development, and research on its core issues can serve as a key breakthrough for promoting the high-quality development of tourism destinations. This study integrated complex adaptive systems theory, path dependency, and complex network theory to construct an "adaptive complexity-path" analytical framework. By combining multi-source heterogeneous data and multidisciplinary theoretical approaches, it developed a comprehensive methodology for constructing business format networks in tourism destinations. Indicators such as path dependency degree and path-breaking degree were introduced to quantitatively analyze the path characteristics of business format network change. Using Jinggangshan City as a case, the study examined the characteristics of change of tourism destination business format networks and its mechanisms during 2012-2022. The results show that: 1) The main business formats in tourism destinations had a prominent influence, driving the formation of a business network dominated by core business formats such as food, accommodation, transportation, sightseeing, shopping, and entertainment and featuring the coordinated development of other related business formats. 2) The interconnections between business formats exhibited differential variations, and the business format network presented a high-proportion weak-link structure. 3) The business format network exhibited a "core-secondary core-periphery" structure, and the hierarchical structure was continuously and dynamically optimized. 4) The evolutionary path of the business format network gradually shifted from path dependence to a coexistence of path dependence and path-breaking. 5) The mechanisms of change of the tourism destination business ecosystem were complex, influenced by a combination of primordial driving forces, innovative driving forces, external pulling forces, external regulatory forces, internal driving forces, and external resistance. This study offers a theoretical basis and illustrative cases to inform the synergistic development of business formats in tourism destinations.

Frequent extreme temperature events pose a serious threat to the sustainable development of counties, and analyzing the relationship between the two from the key concept of social-ecological system—resilience—is one of the issues of key focus. Based on the panel data of 79 counties in Hubei Province from 2010 to 2023, the heterogeneous characteristics of multi-dimensional urbanization were explored on the basis of examining the direct and indirect effects of extreme temperatures on the county-level social-ecological resilience. The study found that: 1) Extreme temperatures measured by the composite index had a significant negative impact on the county-level social-ecological resilience, and there was a "temporal inertia" in the change of the county-level social-ecological resilience. The change of temperature measured by the temperature box showed an asymmetric U-shaped relationship, that is, using 16-20 ℃ as the benchmark interval, on both sides of this temperature interval, the amplitude of the county-level social-ecological resilience decline increased with the growth in the gap between the temperature and the benchmark interval. Under the same range of temperature fluctuation, the county-level social-ecological resilience decline caused by low-temperature shocks was greater. 2) The intensity of impact of extreme temperatures on the county-level social-ecological resilience varied under different urbanization speeds in different dimensions. Compared with the population and spatial attributes, the economic and social attributes of urbanization were more conducive to squeezing the inhibitory effect of extreme temperatures. 3) Labor productivity, the intensity of environmental regulations, and technological innovation respectively played partial mediation, moderating, and single threshold effects in the process of extreme temperatures inhibiting the enhancement of the county-level social-ecological resilience. The empirical evidence provided by this study on the impact of extreme temperatures on the county-level social-ecological resilience can provide a scientific basis for the government to respond positively to sudden perturbations and to strengthen system resilience in order to safeguard the sustainable development of counties.

In recent years, extreme weather has become increasingly common, seriously affecting the daily travel behavior of urban residents. Exploring the travel resilience of urban residents under extreme weather and its influencing factors can help cities actively respond to climate change and become more resilient. However, there is still a significant lack of research on the impact of built environment on travel resilience. This study took Xiamen Island as an example, using taxi trip data and interpretable machine learning method (LightGBM and SHAP) to investigate the travel resilience of urban residents during extreme precipitation events and its relationship with the built environment. The results show that: 1) Extreme precipitation leads to a reduction of about 14.4% in daily travel volume for urban residents, and the response to extreme precipitation showed a time lag. At the same time, travel resilience showed significant spatial heterogeneity. 2) Land use diversity had the highest impact on travel resilience, and all built environment variables were nonlinearly correlated with travel resilience, with interactive effects generated between different built environment variables. Finally, based on the magnitude, range, and combination of impacts of built environment factors on travel resilience, this study proposed precise planning strategies for achieving a climate-adaptive built environment.

Public service facilities constitute the core elements of a city's functional system, and their reasonable spatial layout directly influences urban spatial efficiency and social equity. Traditional extensive models of public service provision are increasingly inadequate to meet residents' growing demands for diversity and higher standards of such services, resulting in an intensified conflict between supply and demand. Taking the main urban area of Nanjing City as a case study and focusing on the 15-minute community living circle concept, this research employed kernel density analysis, network analysis, and the location-allocation (L-A) model to systematically evaluate the current configuration of public service facilities from three dimensions: spatial distribution, coverage level, and supply-demand matching. Optimization strategies were proposed accordingly. The findings reveal that: 1) The spatial distribution of facilities exhibits a core-periphery stratified differentiation, with medical and educational facilities showing multi-core agglomeration, cultural and sports facilities highly concentrated in the central area, and elderly care facilities marginalized and dispersed. 2) The overall coverage level is suboptimal, particularly insufficient in peripheral areas, creating service blind spots. 3) Supply-demand matching analysis indicates a polarization in medical facility allocation, with concurrent overload in the central area and shortages in the periphery for educational, cultural/sports, and elderly care facilities. 4) Optimization using the L-A minimum-facility model significantly enhances the coverage rate of residential points and supply-demand suitability. This study provides a scientific basis for optimizing the allocation of public service facilities and improving the quality and equity of provision, effectively supporting the practical implementation of the 15-minute community living circle concept in fostering urban sustainable development.

The development of new scientific knowledge in a region is imperative for the enhancement of regional independent innovation capacity. While extant studies have focused on the endogenous dynamics of regional scientific knowledge diversification, discussions on the role of external linkages are scarce and controversial. In this study, we incorporated external linkages into the relatedness-complexity framework and systematically investigated the impact of external linkages on the diversification of regional scientific knowledge and its heterogeneous characteristics. Based on the data of highly cited papers from CNKI, key research findings are as follows: 1) The scientific knowledge output of Chinese cities is characterized by the spatial feature of "large dispersion and small agglomeration", with municipalities and provincial capitals producing numerous highly cited papers. The entry of new scientific knowledge occurs more often in ordinary prefecture-level cities, and there is a spatial mismatch between the pattern of scientific knowledge introduction and production in cities. 2) The scientific knowledge base of most Chinese cities is characterized by "high-potential, high-quality" and "low-potential, low-quality" types. Cities with high potential for developing new scientific knowledge also possess scientific knowledge of higher complexity. The backbone network of China's urban scientific knowledge cooperation is characterized by a hierarchical structure. Only cities with high administrative levels, such as municipalities and provincial capitals, have numerous external knowledge linkages, while the external knowledge linkages of ordinary prefecture-level cities are characterized by preferential linkages or geographic proximity. 3) External linkages contribute significantly to regional scientific knowledge diversification, with the share of external linkages contributing to complexity diversification and hindering relatedness diversification, and the geographic diversity of external linkages contributing to relatedness diversification but hindering complexity diversification. 4) The impact of external linkages is characterized by heterogeneity in terms of network location and knowledge base dimensions. The scientific knowledge diversification in the network core region is positively influenced by an increase in geographic diversity of external linkages, while the network peripheral regions are positively influenced by an increase in the share of external linkages. The positive impact of geographic diversity of external linkages is more pronounced than the share of external linkages in the "high-potential, high-quality" regions, while the positive impact of geographic diversity of external linkages is less significant than the share of external linkages in the "low-potential, low-quality" regions. The findings provide policy implications for enhancing scientific knowledge innovation capacity in different regions of China by optimizing external linkages.

China's urban economic network is gradually transforming from a unipolar agglomeration to a polycentric and synergistic structure, driving dynamic adjustments in the interregional industrial division of labor. Revealing the spatiotemporal evolution and influencing mechanisms of advantageous industry overlap under this structural change holds significant theoretical and practical implications for promoting coordinated regional development. This study examined 275 prefecture-level and above cities in China for the years 2012, 2015, and 2017. Using intercity input-output data, it constructed the urban economic network and applied two novel indicators—directed alternative centrality (DAC) and directed alternative power (DAP)—to measure cities' positions within the network. Advantageous industry overlap was quantified through a supernetwork approach. The key findings are as follows: 1) Cities with high DAC and DAP were mainly concentrated in provincial capitals and municipalities with higher levels of economic development. Core cities had continuously strengthened their positions, while low-centrality cities had enhanced mutual connectivity, forming a differentiated network dominated by a few core cities but involving multi-tier linkages across the urban system. 2) The overlap of advantageous industries showed a gradually strengthening convergence effect over time, while spatially it presented a pattern of overall convergence with local divergence, characterized by persistent agglomeration and pronounced regional disparities. 3) Expanding disparities in cities' positions within the directed urban network, as measured by DAC and DAP, significantly reduced both the overlap of leading industries and overall industrial structure similarity, with heterogeneous effects across regions and between resource-based and non-resource-based cities. Further analysis revealed a U-shaped nonlinear relationship between network position disparities and advantageous industry overlap. This research examined the spatiotemporal change of urban network positions and advantageous industry overlap, while clarifying the mechanisms through which directed network status affects industrial convergence. The findings provide a theoretical support for optimizing regional industrial layouts and fostering polycentric and synergistic urban development.

China's excellent tourism cities are the core carriers of the country's tourism development, accounting for over 90% of the national total tourism economic output. They are not only concentrated areas of regional tourism resources and service capabilities but also important representatives of the overall regional image, playing a crucial exemplary and leading role in the development of the tourism industry. In recent years, against the backdrop of frequent global public health emergencies and complex economic fluctuations, tourism economic resilience has become a core topic in tourism research. This study collected relevant data on tourism development of 208 excellent tourism cities across China from 2003 to 2022, and further examined its influencing mechanism on the basis of measuring tourism economic resilience. The study found that the average value of tourism economic resilience of China's excellent tourism cities was generally greater than 0; LISA time path analysis indicated that some excellent tourism cities in the eastern region showed strong spatial dynamics of tourism economic resilience, while those in the central and western regions were relatively weak; the time path curvature was higher in economically developed areas, but lower in inland or late-developing areas. In the LISA spatiotemporal transition, 73.08% of the excellent tourism cities were in a state of self or neighborhood transition, which reflects that the tourism economic resilience of China's excellent tourism cities had significant dynamic change characteristics. Obstacle degree model analysis indicated that the number of students in institutions of higher education, employees in the tertiary industry, and the number of broadband users were the main obstacle factors that affect the tourism economic resilience of China's excellent tourism cities; there was also heterogeneity in the main influencing factors of tourism economic resilience among China's excellent tourism cities in different regions. Based on these conclusions, relevant recommendations for improving the tourism economic resilience of China's excellent tourism cities were put forward.

The industrial agglomeration of digital economy is an important support for promoting green technology innovation, which is of great strategic significance for realizing ecological protection and high-quality development in the Yellow River Basin. Based on the data of digital economy enterprises in 78 prefecture-level cities in the Yellow River Basin from 2011 to 2022, this study used the kernel density estimation and location entropy methods, reciprocal of Herfindahl-Hirschman index, and the two-way fixed effect model to explore the temporal dynamics, spatial patterns, agglomeration characteristics of specialized agglomeration and diversified agglomeration, and their impact on green technology innovation. The results show that: 1) From 2011 to 2022, the number of digital economy enterprises in the Yellow River Basin increased from 36400 to 402100, an increase of about 10.05 times. 2) The spatial distribution of kernel density changed from single-core or dual-core to multi-cores in individual province. The lower reaches formed a contiguous development trend, and the middle and upper reaches showed a scattered distribution of high-value agglomeration areas. The regional differences between specialized agglomeration and diversified agglomeration of digital economy industry were significant, and the overall distribution was high in the east and low in the west. 3) The influence of specialized agglomeration and diversified agglomeration of digital economy industry on green technology innovation showed obvious heterogeneity. Specialized agglomeration had a positive effect on green technology innovation, while diversified agglomeration inhibited green technology innovation in the basin to a certain extent, and there were significant differences in the upstream, midstream, and downstream industries. Based on these results, corresponding countermeasures and recommendations were put forward from the aspects of infrastructure development, industrial planning and layout, and regional cooperation, in order to promote the deep integration of digital economy industry and green technology innovation, and help the high-quality development of the Yellow River Basin.

In the context of global sustainable development and ecological civilization construction, the integration of ecological protection and people's well-being has gradually become a key focus of attention both in China and internationally. In particular, the Yellow River Basin in China, as an important ecological security barrier and economic zone, faces the dual pressure of balancing ecological protection and economic development. Ecological well-being performance is a comprehensive index to evaluate ecological protection and people's well-being. Improving ecological well-being performance is an objective requirement for ecological protection and high-quality development of the Yellow River Basin. Based on the reconstruction of an ecological well-being performance evaluation indicator system, this study used the Super-EBM model considering the undesirable outputs to quantitatively measure ecological well-being performance in the Yellow River Basin during 2005-2022, and used kernel density analysis and exploratory spatial data analysis methods to describe the characteristics of change of the spatial and temporal patterns of ecological well-being performance in the region. Finally, the fsQCA method was used to analyze the configuration mechanism of ecological well-being performance. The findings are as follows: 1) During the research period, the ecological well-being performance of the Yellow River Basin generally showed a continuous upward trend, but regional differences were significant, presenting a multi-level differentiation trend and complex evolution characteristics. 2) The ecological well-being performance in the Yellow River Basin presents a staged pattern of high in the east and low in the west, and high in the south and low in the north. The positive spatial autocorrelation has been enhanced, and the spatial disequilibrium and spatial agglomeration characteristics are significant. 3) In terms of configuration mechanism, three driving mechanisms can be identified: single dominance type, dual interaction type, and multiple cooperation type. Two limiting mechanisms exist: digital technology-science and technology deficiency type, and science and technology-environmental regulation deficiency type. The research results can provide a scientific reference for promoting regional ecological well-being performance.

Rural development is currently undergoing a pivotal shift from a resource-dependent model to one driven by innovation. The rural-urban reverse population flows have become a key factor in addressing the long-standing challenges of rural innovation and development. Using the input-support-output rural innovation efficiency framework, along with the moderating effect and multiscale geographically weighted regression (MGWR) methods, we analyzed the change of spatial pattern of rural-urban reverse population flows and rural innovation efficiency of 27 administrative villages in Luotuoao Town, Hubei Province—a typical rural-urban reverse population flow area—from 2018 to 2020. We also explored the impact of the rural-urban reverse population flows on rural innovation. The results show that: 1) The innovation level and the distribution of the rural-urban reverse population flow in each village of Luotuoao Town exhibited significant spatial imbalances, with some spatial correlation. 2) The counterflow population between urban and rural areas played a significant role in enhancing innovation in rural areas. It exerted the greatest influence on innovation input, with a spatial distribution characterized by a dual-core architecture and gradual reduction. 3) The impact of rural-urban reverse population flows on rural innovation is influenced by various factors and shows regional variation. Industrial structure, agricultural cooperatives, and nighttime light intensity all have positive effects. Additionally, low-altitude areas with dense road networks facilitate the flow and application of innovation resources, thereby boosting the innovation capacity of reverse migration populations. This study offers a theoretical support for building a sustainable mechanism to attract and retain rural talents.

Although ecological villages in the suburbs of metropolis can promote development by virtue of the spillover effect of the central urban area and the advantages of ecological landscape resources, they are faced with development bottlenecks such as hollowing out and limited transformation of ecological values due to the siphon effect and ecological controls. Taking Chayuan Village, an ecological village in Hubei Province in 2023, as an example, this study analyzed the characteristics and internal mechanisms of spatial transformation of ecological villages in metropolitan suburbs by using the embeddedness theory. The study found that: 1) Constructing a theoretical analysis framework from the four dimensions of structural embeddedness, relational embeddedness, institutional embeddedness, and cultural embeddedness can lay a foundation for analyzing the internal mechanisms of rural spatial transformation under the interaction of social system and agents. 2) The remarkable characteristics of rural spatial transformation are embodied in the orderly expansion of material space, the compound function of economic space, the pluralistic and open social space, and the richness and co-creation of cultural space. 3) With regard to the rural space transformation mechanisms, the position of the village in the social network, the connection strength of social relations, the intervention strength of the policy system, and the cultural and ideological situation of village residents deeply affect the process of rural space transformation. The modernization of village material space and the traditionalization of economic space and ideas coexist in the initial exploration stage under the weak relationship embedding. The upgrading of rural space in the slow development stage under the strong system embedding was limited, and the rural space transformation in the structural reorganization stage under the multiple embedding coordination has achieved some success. The research on the characteristics and mechanisms of ecological village spatial transformation in metropolitan suburbs is helpful for promoting their high-quality development.